Utilizing data from multiple studies (meta-analysis) to determine effective dose-duration levels. Example: rats and mice exposed to hydrogen sulfide.
The objective of this exercise was to incorporate as much data as possible from multiple studies, that may differ in exposure durations, to derive a chemical-specific dose-duration response curve from which to identify toxicity markers (e.g., ED01, benchmark dose, and LD50). This has the advantage of incorporating more information than single-study assessments to improve estimates and reduce confidence intervals, and determining toxicity markers as functions of exposure duration as well as dose. The example used mortality for rats and mice, analyzed separately, from acute exposure to hydrogen sulfide (dose refers to airborne concentration of H(2)S). Statistical methods were applied to determine when data from different studies could be pooled. EC01, EC10, and EC50 (doses with response rates of 1, 10, and 50%) were estimated, with 95% confidence intervals, at durations of 5, 10, and 30 min, and 1, 2, 4, and 6 h. A single dose-duration response curve for mortality was fit to the rat data for exposures of 5 min, 10 min, 30 min, and 1h, using a logistic curve additive in log(dose) and log(duration). Separate fits of that model were required, however, at 2, 4, and 6h, due to an increasing impact of duration relative to concentration as duration increased. The curves for rats fit the data exceedingly well and exhibited a threshold-like response followed by a steep incline as concentration increased. There were fewer data for mice but the response pattern for mortality clearly differed from rats. This example demonstrates the feasibility of extending the concept of single-study benchmark doses to multiple-study dose-duration benchmarks, using U.S. EPA's program CatReg. Similar applications to long-term animal studies could be considered.